Welcome back to a new post at thoughts-on-cpp.com. In this post, I would like to discuss the Gauss integration algorithm, more precisely the Gauss-Legendre integration algorithm. The Gauss-Legendre integration is the most known form of the Gauss integrations. Others are
- Gauss-Tschebyschow
- Gauss-Hermite
- Gauss-Laguerre
- Gauss-Lobatto
- Gauss-Kronrod
The idea of the Gauss integration algorithm is to approximate, similar to the Simpson Rule, the function f(x) by

While w(x) is a weighting function,
is a polynomial function (Legendre-Polynomials) with defined nodes
which can be exactly integrated. A general form for a range of a-b looks like the following.

The Legendre-Polynomials are defined by the general formula and its derivative


The following image is showing the 3rd until the 7th Legendre Polynomials, the 1st and 2nd polynomials are just 1 and x and therefore not necessary to show.

Let’s have a closer look at the source code:
The integral is done by the gaussLegendreIntegral
(line 69) function which is initializing the LegendrePolynomial
class and afterward solving the integral (line 77 – 80). Something very interesting to note: We need to calculate the Legendre-Polynomials only once and can use them for any function of order n in the range a-b. The Gauss-Legendre integration is therefore extremely fast for all subsequent integrations.
The method calculatePolynomialValueAndDerivative
is calculating the value (line 50) at a certain node
and its derivative (line 51). Both results are used at method calculateWeightAndRoot
to calculate the the node
by the Newton-Raphson method (line 33 – 37).

The weight w(x) will be calculated (line 40) by
![w_{i}=\frac{2}{\left(1-x_{i}^{2}\right)\left[P_{n}^{\prime}\left(x_{i}\right)\right]^{2}} w_{i}=\frac{2}{\left(1-x_{i}^{2}\right)\left[P_{n}^{\prime}\left(x_{i}\right)\right]^{2}}](https://s0.wp.com/latex.php?latex=w_%7Bi%7D%3D%5Cfrac%7B2%7D%7B%5Cleft%281-x_%7Bi%7D%5E%7B2%7D%5Cright%29%5Cleft%5BP_%7Bn%7D%5E%7B%5Cprime%7D%5Cleft%28x_%7Bi%7D%5Cright%29%5Cright%5D%5E%7B2%7D%7D++&bg=%23ffffff&fg=%23383838&s=2)
As we can see in the screen capture below, the resulting approximation of

is very accurate. We end up with an error of only
. Gauss-Legendre integration works very good for integrating smooth functions and result in higher accuracy with the same number of nodes compared to Newton-Cotes Integration. A drawback of Gauss-Legendre integration might be the performance in case of dynamic integration where the number of nodes are changing.

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